Librería: Ria Christie Collections, Uxbridge, Reino Unido
EUR 152,34
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Añadir al carritoCondición: New. In.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 213,97
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. 1st ed. 2021 edition NO-PA16APR2015-KAP.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030611108 ISBN 13: 9783030611101
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examplesincluded in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 238,01
Cantidad disponible: 2 disponibles
Añadir al carritoHardcover. Condición: Brand New. 204 pages. 9.25x6.10x0.71 inches. In Stock.
Librería: Mispah books, Redhill, SURRE, Reino Unido
EUR 229,22
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Añadir al carritoHardcover. Condición: New. NEW. SHIPS FROM MULTIPLE LOCATIONS. book.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 126,26
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Idioma: Inglés
Publicado por Springer International Publishing Nov 2020, 2020
ISBN 10: 3030611108 ISBN 13: 9783030611101
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 160,49
Cantidad disponible: 2 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examplesincluded in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences. 204 pp. Englisch.
Idioma: Inglés
Publicado por Springer International Publishing, 2020
ISBN 10: 3030611108 ISBN 13: 9783030611101
Librería: moluna, Greven, Alemania
EUR 136,16
Cantidad disponible: Más de 20 disponibles
Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Introduction to metaheuristic techniques and algorithms, biomimicry and nature-inspired algorithms with swarm intelligence and presents the basics of the algorithmsProvides a guide of how to develop algorithms from nature-insp.
Idioma: Inglés
Publicado por Springer, Palgrave Macmillan Nov 2020, 2020
ISBN 10: 3030611108 ISBN 13: 9783030611101
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 160,49
Cantidad disponible: 1 disponibles
Añadir al carritoBuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book exemplifies how algorithms are developed by mimicking nature. Classical techniques for solving day-to-day problems is time-consuming and cannot address complex problems. Metaheuristic algorithms are nature-inspired optimization techniques for solving real-life complex problems. This book emphasizes the social behaviour of insects, animals and other natural entities, in terms of converging power and benefits. Major nature-inspired algorithms discussed in this book include the bee colony algorithm, ant colony algorithm, grey wolf optimization algorithm, whale optimization algorithm, firefly algorithm, bat algorithm, ant lion optimization algorithm, grasshopper optimization algorithm, butterfly optimization algorithm and others. The algorithms have been arranged in chapters to help readers gain better insight into nature-inspired systems and swarm intelligence. All the MATLAB codes have been provided in the appendices of the book to enable readers practice how to solve examplesincluded in all sections. This book is for experts in Engineering and Applied Sciences, Natural and Formal Sciences, Economics, Humanities and Social Sciences.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 204 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 226,88
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. Print on Demand.
Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 225,06
Cantidad disponible: 4 disponibles
Añadir al carritoCondición: New. PRINT ON DEMAND.